Functions beyond biomass reveal global mismatch in coral reefs

(title not final at all)

At a glance

  • In times of extreme human impacts on natural systems, conservation strategies focus on maximizing function and multifunctionality. Such an economics approach pertains mostly to terrestrial systems. Fish contribute to a high proportion of consumer biomass and are important for coral reef functioning and human livelihood. Yet, the effect of community structure and species identity on functioning remains poorly understood. It is crucial to understand the community drivers of functions in order to guide management targets towards the conservation of coral reef functioning.
  • Beyond biomass, there is still a large variation of 5 key functions that needs to be considered
  • Quantifying functions reveals a mismatch between the different functions (fig. 1), that is driven by differences in community structure (fig. 2). As a consequence, the idea of maximizing all functions to reach multifunctionality is an illusion.
  • Even though there is a high degree of species dominance for each function across all communities (fig.3, left), global keystone species do not exist. Instead, most species are occasional keystones (fig.3, middle) that are most vulnerable to fishing (fig. 4).
  • Our results suggest that current local and global conservation objectives for coral reefs and other marine ecosystems need to be reconsidered: management for functionality and targeted conservation of species need to be adjusted for local conditions and needs, but holistic protection of a diverse pool of species will increase the likelihood of sustaining critical ecological processes.

Main figures

Figure 1: World maps of five key ecosystem functions. Dots indicate the localities that are included in this study. Dot size represents the average of the residuals of each log-transformed function after regression with the log-transformed standing biomass and sea surface temperature. Similarly, the color scales show the value of the residuals categorically (low = lower 20%, medium = 20-80%, high = >80%). Squares indicate the five localities with the highest average residuals of multifuctionality. Circles highlight the five localities with the highest average residuals of each function respectively.

Figure 2: a: Slope values of the Bayesian linear regression for each function with community variables. The log-transformed standing biomass was also included as a covariable, but not shown in this figure. All data was standardized to be able to compare across functions and variables. Functions were log-transformed before standardisation. b-d: Marginal effect plots, where each predicted value was normalised a posteriori. The solid black line represents the multifunctionality.

Figure 3: Left: Distribution of the degree of dominance of communities per function. A degree of dominance of 0 means each species contributes equally to a function, 1 means a single species performs a function. Middle: Distributions of frequency of being important to each function of all species. A value of 1 thus means that a species is always important whenever present. A species is counted as being important in a community if that species contributes to more than 1 divided by the species richness. Dots represent the median value, while lines indicate the interquartile range. Right: Heat maps of median family-level contributions to each function per bioregion. Only the nine most important families are shown here. CIP = Central Indo-Pacific, CP = Central Pacific, EA = Eastern Atlantic, EP = Eastern Pacific, WA = Western Atlantic, WI = Western Indian  

Figure 4: Vulnerability and importance to each function of fish species included in this study. Transparant bars represent the relative number of species in each category of vulnerability. Filled bars show the proportion of species that are locally important (i.e. perform more than 1/N of the function, where N is the number of species observed in a certain transect).

Outline

1) Introduction (1 or 2 paragraphs)

Ecosystem functioning and services in times of extreme human impacts; maximizing function and multifunctionality is the hallmark of many conservation strategies and calls from scientist, mostly derived from an ecosystem economics approach (maximize function and services). However, this pertains predominantly to grasslands, forests and other heavily managed, cultivated systems. Marine ecosystems differ dramatically from terrestrial by being much less manageable; coral reefs provide tremendous services and are one of the most vulnerable ecosystems worldwide. Fishes are the most important consumer taxon, have a close relationship with corals, and are a critical source of livelihoods.

  • First challenge is to properly define function
  • We know that more biomass = more function, more sst = more function
  • Beyond biomass and temperature, what defines functioning?
  • Here we quantify 5 key processes: N excretion, P excretion, production, herbivory, piscivory
  • 2 targets:
    1. functions beyond biomass
      how does community structure affect functioning? Can all functions be maximized?
    2. Species identity and vulnerability
      Are there a consistent set of species that are more important than others and how vulnerable are “important” species to fishing and climate change (habitat destruction)?

2) Summary

Here, we show that, superficially equal fish communities on the world’s coral reefs can vary up to 100-fold in their functionality, depending on various aspects of their community structure. However, due to inherent biological trade-offs, no single configuration can maximize all functions. Furthermore, we reveal unpredictable local functional dominance by a wide range of species, changing contributions of families to ecological processes, and varying vulnerabilities of processes to fishing and climate-related stressors. Our results suggest that current local and global conservation objectives for coral reefs and other marine ecosystems need to be reconsidered: management for functionality and targeted conservation of species and community structure need to be adjusted for local conditions and needs, but holistic protection of a diverse pool of species will increase the likelihood of sustaining critical ecological processes.

3) Communities: Mismatch between functions ~ ecological drivers

  • All functions are definitely related to biomass, but for communities with similar biomass, functions can still vary up to 10- to 1000-fold (fig. S1a).
  • Beyond biomass, there is a mismatch between the different functions (fig1) with some functions being negatively correlated (fig. S1b, fig. S2)
  • Trophic, size, and age structure affect functions in different ways (fig.2, a)
  • Maximizing “multifunctionality” is defined by intermediate values of certain community variables. (fig2:b,c,d)

4) Role of species identity: dominance and vulnerability

  • Locally there is often a high degree of dominance, i.e. a couple of species perform most of the function. (A bit less for herbivory-> more complementary) (fig3, left)
  • Globally, absolute keystone species rarely exist, most species (~70%) are locally important (fig. 3, middle). This is supported by fitting beta distributions per species (a species with high phi and mu does not exist, i.e. no species consistently has a high contribution to a function, fig. S3). On the other hand about 70% of all species are locally important.
  • On the family level, across geographical regions there is some variation in the contributions to functions, and there is variability within the same region across functions (fig3, right)
  • Important species are generally more vulnerable to fishing, double jeapardy seems rare (fig.4) Most herbivores and piscivores are important somewhere, species important to piscivory are most vulnerable to fishing, there’s an considerable proportion of herbivores that has lower vulnerability compared to other functions (fig4).

5) Discussion human impact on community structure and functioning

  • We know that multiple human stressors are causing species to decline, and are affecting the size, age, and trophic structure of fish communities.
  • More details about human impact on community structure, and how in turn that affects functioning.
  • Indeed, we see that N excretion and production increase with human impact (fig. S4) (see also Morais as example).
  • Due to the observed mismatch, it is untenable to achieve maximized values for all functions. Relate to other (terrestrial) ecosystems.
  • The effect of potential extinctions of species varies across locations. Provide an example? For most species, total extinction would have a big effect on functioning somewhere.

6) Consequences for conservation

    1. Important to consider multiple functions beyond biomass. Only looking at N excretion for example would give va biased view. Maximized function does not nescessarily represent a “healthy” ecosystem. We need to step away from economics approach and define conservation targets locally.
      Examples:
    • Reefs that are most crucial for fishing -> Maximize biomass production
    • Reefs that are succeptible to algae growth -> Maximize herbivory
    • Reefs that are vulnerable to bleaching -> Maximize P excretion
    1. Secondly, species important for the different functions are not the same ones across locations. Most species are occasionally important, but none are always important. Species conservation targets cannot be generalized globally. Species importance and conservation should be planned locally, taking into acount historical knowledge (i.e. some species that are rare/depleted may have played an important role in the past)
    1. Third, important species seem to be most vulnerable to fishing. Local fisheries management may prioritize species that are extra vulnerable. Note that also long-term effects of habitat loss will affect a greater amunt of species than presented herein so there is no doubt that climate change should be targeted by global action.
  • Thus, conservation needs to be planned locally and in general we essentially want to conserve all species

Supplementary figures

Figure S1: a) Fold variation of each function per biomass class of 50g/m2 across fish communities. b) Correlation matrix of the residuals of the five functions.

Figure S2: Scatter plots of residuals of all functions and multifunctionality.  

Figure S3: Relationship of parameters mu and phi of the fitted beta distributions per species per function. Beta distributions were fitted with random effects for sites and localities.
 

Figure S4: Predicted residuals of each function with varying gravity to fish markets.